1. Field of the Invention
The invention relates to a color measuring system and method employing fuzzy logic, classifier templates and super ellipsoids for the purpose of defining acceptability tolerances for color and appearance with subsequent rating of other samples as pass or fail.
2. Description of the Related Art
The problem of defining acceptable tolerances for the color and appearance differences of product taken from a production line is a difficult task. The decision has to be a subjective one since the criteria is visual acceptability and not visual perceptibility. If the tolerances are set too large, the result can be returned product from the field. If the tolerances are set too small, the cost to produce the acceptable product could become prohibitive.
U.S. Pat. No. 4,745,555, a continuation of U.S. Pat. No. 4,688,178, describes the use of color tolerances for the purpose of shade sorting textile fabric. Color tolerances are defined by ellipsoids and are used to classify and place samples according to their color differences from a standard color target in such a way as to minimize the use of samples that lie farthest from the target. Further, the described method only makes use of existing tolerances, and does not appear to provide any capability for defining the acceptability tolerance itself. Only conventional ellipsoid definitions are used to define the color tolerances and, therefore, the definition of color tolerance is limited.
Of possible limited relevance to the invention are the disclosures in U.S. Pat. Nos. 4,697,242; 4,881,178; 4,918,618; 4,935,877 and 5,048,095. These patents cover applications for different types of artificial intelligence such as genetic algorithms and neural networks.
"Docking a Truck: Fuzzy," an article in AI Expert, May 1992, describes a typical use of fuzzy logic. The basic concept of fuzzy sets is that the entire domain of possible observation values is subdivided into a smaller number of subsets. These subsets are usually overlapping, so that a particular observation point may be a partial member of more than one subset. That is, the boundaries to the subsets are fuzzy rather than sharp. Each fuzzy subset is associated with a set of rules that allow for a corresponding action of the proper magnitude and direction. The organization of many subsets into a single result is called defuzzification. In the case of the above article, fuzzy logic is used to transform spatial position into instructions defining the direction and amount to turn a vehicle steering wheel along with information regarding the proper truck velocity to reach the desired spatial position.
The publications, "CCM System Utilizing a Neural Network," Dyeing and Finishing Technology, Vol. 26, No. 8, pp 553-557, and, "Neural Networks in the Colour Industry," Applications of Artificial Intelligence in Engineering, Volume V, 1991, describe the use of fuzzy logic and another artificial intelligence method, namely neural networks, in the area of color. The term CCM stands for Computer Color Matching, which establishes colorant formulations to match specific color targets. Fuzzy logic is used to replace conventional algorithms that determine the colorant formula, while the neural network is used to replace the traditional Kubelka-Munk optical theory of color mixing. While this disclosure describes the practical use of artificial intelligence tools in the area of color, it does not appear to teach or suggest the use of such tools to quantify acceptability tolerances of color and appearance perception for use in classifying subsequent samples for pass and fail. Another publication of possible interest is "Conversion of a Visual to an Instrumental Color Matching System: An Experimental Approach" by R. Vanderhoven, Textile Chemist and Colorist, May 1992, Vol. 24, No. 5 , pages 19-25. This represents an attempt to go from a visual to instrumental approach for shade sorting, but the conclusion of the publication was that this approach did not agree well with visual observations.
The need to quantify the visual acceptability tolerances for specific colors so that the tolerances can be used to classify subsequent samples is a desirable operation in the production of colored products. Previous technologies have depended upon the user to provide the tolerances by whatever techniques thought practical. The chosen tolerances might represent rectangular as well as ellipsoidal volumes, even if the visual assessments did not agree. While the user could make a single judgment for a single sample as to its acceptability, he usually found it difficult to express a practical three dimensional tolerance for the total color acceptability of the color. The use of standard ellipsoids as the acceptability volume provides better visual agreement than rectangular volumes. However, it still does not agree well with visual perception on borderline situations especially when the specimens are not flat, uniform or opaque.